惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

小众软件
小众软件
MyScale Blog
MyScale Blog
N
News and Events Feed by Topic
IT之家
IT之家
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
有赞技术团队
有赞技术团队
T
The Blog of Author Tim Ferriss
The Cloudflare Blog
博客园 - 聂微东
Apple Machine Learning Research
Apple Machine Learning Research
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
美团技术团队
V
Visual Studio Blog
M
MIT News - Artificial intelligence
V
V2EX
博客园_首页
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Blog — PlanetScale
Blog — PlanetScale
F
Full Disclosure
H
Help Net Security
MongoDB | Blog
MongoDB | Blog
博客园 - 叶小钗
S
SegmentFault 最新的问题
博客园 - 三生石上(FineUI控件)
D
Docker
Engineering at Meta
Engineering at Meta
博客园 - Franky
aimingoo的专栏
aimingoo的专栏
Jina AI
Jina AI
N
Netflix TechBlog - Medium
宝玉的分享
宝玉的分享
大猫的无限游戏
大猫的无限游戏
人人都是产品经理
人人都是产品经理
云风的 BLOG
云风的 BLOG
博客园 - 司徒正美
I
InfoQ
G
Google Developers Blog
L
LangChain Blog
F
Fortinet All Blogs
博客园 - 【当耐特】
Hugging Face - Blog
Hugging Face - Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
WordPress大学
WordPress大学
A
Arctic Wolf
Martin Fowler
Martin Fowler
G
GRAHAM CLULEY
L
LINUX DO - 热门话题
C
Cisco Blogs
Y
Y Combinator Blog
罗磊的独立博客

Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - February 2026 Amazon EC2 security: How misconfigured and public AMIs expand your cloud attack surface Enable end-to-end visibility into your Java apps with a single command Measure and improve mobile app startup performance with Datadog RUM Evaluating our AI Guard application to improve quality and control cost Identify untested code across every level of your codebase Make use of guardrail metrics and stop babysitting your releases Monitor Versa Networks SD-WAN performance in Datadog Improve performance and reliability with APM Recommendations Remediate transitive vulnerabilities faster with Datadog Software Composition Analysis Generate audit-ready vulnerability and compliance reports with Datadog Sheets Monitor Fortinet FortiManager performance in Datadog Improve test coverage across codebases with Datadog Code Coverage Move fast, don’t break things: Consistent testing standards at scale Enrich logs with ServiceNow CMDB context before routing to any SIEM or logging tool Monitor Lustre with Datadog Make faster, better product decisions with Datadog Product Analytics Surface and remediate runtime posture issues with Workload Protection Findings Protect agentic AI applications with Datadog AI Guard How to optimize JavaScript code with CSS Trace Google Pub/Sub workloads in Cloud Run with Datadog Detect human names in logs with ML in Sensitive Data Scanner How we cut our NLQ agent debugging time from hours to minutes with LLM Observability Debug PostgreSQL query latency faster with EXPLAIN ANALYZE in Datadog Database Monitoring Datadog acquires Propolis Unify and correlate frontend and backend data with retention filters Scale compliance across global frameworks with Datadog Cloud Security Monitor Arista VeloCloud SD-WAN performance with Datadog Building reliable dashboard agents with Datadog LLM Observability Simplify log collection and aggregation for MSSPs with Datadog Observability Pipelines Mitigation for Node.js denial-of-service vulnerability affecting Datadog APM Automate flaky test fixes with the Bits AI Dev Agent and Test Optimization How we built an AI SRE agent that investigates like a team of engineers Datadog integrations 2025 recap: Observability for AI, security, and hybrid cloud Design effective executive dashboards with Datadog Implement dbt data quality checks with dbt-expectations Bring faster visibility into AWS Lambda functions with remote instrumentation Troubleshoot faster with the GitLab Source Code integration in Datadog How Cambia Health Solutions saved $30,000 monthly with Cloud Cost Management and the Datadog Resource Catalog Normalize any logs for Cloud SIEM with Datadog's OCSF processor Optimizing Datadog at scale: Cost-efficient observability at Zendesk Detect, diagnose, and resolve network issues easily with CNM Network Health Connect engineering errors to user impact in early-stage products Cilium configuration for Kubernetes operations at scale Designing feedback loops for progressive delivery Ship features faster and safer with Datadog Feature Flags Choosing the right OpenTelemetry Collector distribution Route your monitor alerts with Datadog monitor notification rules Automate Cloud SIEM investigations with Bits AI Security Analyst Cloud threat detection: How to identify risky activity across control and data planes Collecting Kafka performance metrics Monitoring Kafka with Datadog Monitoring Kafka performance metrics
Run Datadog Synthetic tests in Azure Pipelines
2022-09-30 · via Datadog | The Monitor blog

Continuous integration (CI) demands continuous testing: shifting left helps prevent faulty code from spreading, which is one of the core aims of CI. Datadog’s new Azure DevOps extension enables you to seamlessly incorporate integration and end-to-end tests into existing CI/CD workflows on Azure Pipelines, a dedicated CI/CD service that automatically runs builds, performs tests, and deploys your services and applications via cloud-hosted pipelines. By incorporating these tests using Datadog Synthetic Monitoring, you can bolster your shift-left strategy and proactively assess user experience at each step of your development process.

In this post, we’ll guide you through setting up the extension and implementing end-to-end tests in Azure Pipelines with our synthetic testing and monitoring solution.

Add synthetic tests to your existing Azure Pipelines

Datadog Synthetic Monitoring allows you to continuously assess the performance of your applications and services by running simulated user requests and actions from locations around the world. Synthetics enable you to use a single suite of tests in your production, staging, and development environments, in order to streamline your CI/CD processes and ensure a consistent user experience.

Incorporating Datadog Synthetic Monitoring in your Azure Pipelines environments is fast and code-free. Its simple-to-use interface enables anyone on your team, regardless of their coding experience, to create integration and end-to-end tests. The extension can be configured to test any URL at any and every point on your pipeline, including your QA, staging, pre-production, and production environments.

To begin, find the Datadog CI Extension in the Visual Studio marketplace and install it in your Azure organization. Next, create a Datadog CI service connection in your Pipelines project, and either input your API and application keys there or add them as secret variables in your Pipelines project.

Configuring tests in Azure Pipelines.
Configuring tests in Azure Pipelines.
Configuring tests in Azure Pipelines.

You can then find and use the SyntheticsRunTests task in the pipeline tasks side panel of Azure Pipelines. Here, you can also configure complex tasks by adding custom start URLs, login credentials, and test data as variables. Doing so will apply these variables to all of the tests that you run in your pipeline. Alternatively, you can add custom variables on a test-by-test basis by providing a custom configuration file. Refer to the extension’s documentation for more information on configuring tasks.

Monitor Synthetic test results and CI pipeline performance in Datadog

Once you’ve set up the extension and configured some tests, you can use our CI Results Explorer to examine the results of those tests in Datadog. The explorer displays a status and duration for each test batch, as well as details on individual test runs, letting you compare the results of tests running in different browsers, devices, and locations. These results highlight issues such as regressions, broken features, or suboptimal application performance, helping you ensure that any faulty code is identified and corrected before it can make it to production.

Analyze test results in the CI Results Explorer.

For deeper insight into your CI pipelines themselves, Datadog CI Visibility uses key health and performance metrics to help you optimize your workflows. CI Visibility identifies high error rates, excessive build durations, flaky tests, and more, parsing pipeline performance by individual stages and jobs to help you zero in on snags and expedite troubleshooting.

Get started with Datadog Synthetic Monitoring for Azure Pipelines

With the Datadog CI Extension for Azure Pipelines, you can now easily incorporate Datadog Synthetic testing and monitoring into your CI pipelines in order to test your application workflows earlier and more frequently throughout the development process. Pairing Synthetic Monitoring with CI Visibility can deepen your insight by augmenting your integration and end-to-end tests with key pipeline performance metrics.

Datadog offers visibility solutions for a wide range of CI providers, with integrations for Jenkins, CircleCI, and GitHub Actions in addition to Azure Pipelines. You may also want to learn more about Datadog CI Visibility and incorporating Datadog Synthetic Monitoring in any kind of CI/CD pipeline. If you’re an Azure Pipelines user and an existing Datadog customer, download the Datadog CI Extension from the Visual Studio marketplace to get started with synthetic testing and monitoring in your pipelines today. Or, if you’re brand new to Datadog, use the extension with our 14-day free trial.